Mining of Topographic Feature from Heterogeneous Imagery and Its Application to Lunar Craters View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2002-03-14

AUTHORS

Rie Honda , Yuichi Iijima , Osamu Konishi

ABSTRACT

In this study, a crater detection system for a large-scale image database is proposed. The original images are grouped according to spatial frequency patterns and both optimized parameter sets and noise reduction techniques used to identify candidate craters. False candidates are excluded using a self-organizing map (SOM) approach. The results show that despite the fact that a accurate classification is achievable using the proposed technique, future improvements in detection process of the system are needed. More... »

PAGES

395-407

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/3-540-45884-0_29

DOI

http://dx.doi.org/10.1007/3-540-45884-0_29

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1025313127


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